A typical data center may consist of a large number of physical computers and virtual machines. These computing resources service hundreds of software applications that cater to a large number of users on a twenty four by seven basis. Misconfigured software and hardware are one of the leading causes of failure in large modern data centers. The administrators of these data centers must constantly track configuration changes across millions of configuration items (CIs), always on the lookout for changes that may soon be or may have recently caused problems. Once they find configuration problems, they must be able to easily communicate these problems, or the trends that created the problems, to their peers and superiors, to justify corrective measures. Currently, the drift visualizations available to process this data are insufficient for the task. They either show only a limited amount of data, or merely list all the data associated with all changes in the data center environment. In neither case can the administrator easily pick relevant changes out of the summation of the information available, or easily identify and communicate negative configuration trends that imply larger administrative problems.